This past year I got involved with Software Carpentry, a group which teaches basic research computing to scientists. I’ve helped Stephen Turner teach a few RNA-Seq workshops through UVA’s BioConnector, and last March I taught my first independent-from-Stephen workshop with two other UVA instructors, Alex Koeppel and Zhuo Fu.
Teaching basic shell programming!
Look, up here at this line!
We had such a good time working together and with Bart Ragon and VP Nagraj from the UVA Health Sciences Library that we decided to keep meeting in this awesome HSL room every week.
Yes, that’s TWO screens for coding.
Doesn’t it look like the bridge of the Enterprise? Make it so.
At first we decided to keep meeting in order to review and debug each other’s code, but then I had a brainwave. Perhaps we could work on an independent project together?
We all have a basic familiarity with programming in R, so that seemed like the language of choice. At first I had envisioned some interactive modifications to LocusZoom
— something along the lines of an app where you can learn more about particular SNPs by clicking or hovering over their representations on a graph. However, upon sober reflection, I realized that I am the only one in the main group that works in genomics, and the required amount of domain-specific background knowledge would be extremely high. Additionally, fiddling with such a feature rich program like LocusZoom might not make for a great starter project.
As part of my position at Public Health Sciences I work with both the Center for Public Health Genomics (CPHG) and the Institute of Law, Psychiatry and Public Policy (ILPPP). The specific project that I work on involves analyzing court data pertaining to mental health proceedings in the State of Virginia. It’s a very different domain from my other bioinformatics work, but it ends up being a perfect fit as a project to cut our teeth on app construction with R. The data tables are fairly straightforward, even if deeper understanding requires further domain knowledge. Also, there would be actual immediate public policy benefits to having interactive and layered representations of the data. (e.g. allowing lawmakers to see up-to-date graphs of commitment trends in their specific districts.)
So, from now on, the inter-departmental SWC project group (cool nickname pending), along with my colleague, Ashleigh Allen from the ILPPP, will be spending weekly meetings brainstorming/planning/building an app. We’re researching various R packages to help us toward our goal. Right now we are considering shiny.
I’ll keep both of my readers up to date on our project as it takes shape!